Local elastic strain and strain tensor measurements of deformed metals using focused, submicrometer Xrays

The use of depth resolved, submicrometer X-ray beams for studying deformation microstructures in plastically deformed metals has come a long way over the past 5 years. We can identify phases, measure crystallographic orientations, and measure lattice constants from buried, submicrometer sample volumes throughout extended sample regions within single crystal and polycrystalline samples. In special cases, we can also measure both deviatoric and complete elastic strain tensors with reliable uncertainty estimates for the tensor components. Examples of these capabilities will be described, including nondestructive, full strain tensor measurements from through-Si vias in microelectronics, and strain measurements from commercial Al alloys deformed using equal-channel angular pressing. Expectations for the future will also be discussed

Epidermal growth factor targeting of bacteriophage to the choroid plexus for gene delivery to the central nervous system via cerebrospinal fluid

Because the choroid plexus normally controls the production and composition of cerebrospinal fluid and, as such, its many functions of the central nervous system, we investigated whether ligand-mediated targeting could deliver genes to its secretory epithelium. We show here that when bacteriophages are targeted with epidermal growth factor, they acquire the ability to enter choroid epithelial cells grown in vitro as cell cultures, ex vivo as tissue explants or in vivo by intracerebroventricular injection. The binding and internalization of these particles activate EGF receptors on targeted cells, and the dose- and time-dependent internalization of particles is inhibited by the presence of excess ligand. When the phage genome is further reengineered to contain like green fluorescent protein or firefly luciferase under control of the cytomegalovirus promoter, gene expression is detectable in the choroid plexus and ependymal epithelium by immunohistochemistry or by noninvasive imaging, respectively. Taken together, these data support the hypothesis that reengineered ligand-mediated gene delivery should be considered a viable strategy to increase the specificity of gene delivery to the central nervous system and bypass the blood-brain barrier so as to exploit the biological effectiveness of the choroid plexus as a portal of entry into the brain

DrosoPhyla: Resources for Drosophilid Phylogeny and Systematics.

The vinegar fly Drosophila melanogaster is a pivotal model for invertebrate development, genetics, physiology, neuroscience, and disease. The whole family Drosophilidae, which contains over 4,400 species, offers a plethora of cases for comparative and evolutionary studies. Despite a long history of phylogenetic inference, many relationships remain unresolved among the genera, subgenera, and species groups in the Drosophilidae. To clarify these relationships, we first developed a set of new genomic markers and assembled a multilocus data set of 17 genes from 704 species of Drosophilidae. We then inferred a species tree with highly supported groups for this family. Additionally, we were able to determine the phylogenetic position of some previously unplaced species. These results establish a new framework for investigating the evolution of traits in fruit flies, as well as valuable resources for systematics

STAG2 is a clinically relevant tumor suppressor in pancreatic ductal adenocarcinoma

Background Pancreatic ductal adenocarcinoma (PDA) is a highly lethal cancer characterized by complex aberrant genomes. A fundamental goal of current studies is to identify those somatic events arising in the variable landscape of PDA genomes that can be exploited for improved clinical outcomes. Methods We used DNA content flow sorting to identify and purify tumor nuclei of PDA samples from 50 patients. The genome of each sorted sample was profiled by oligonucleotide comparative genomic hybridization and targeted resequencing of STAG2. Transposon insertions within STAG2 in a KRASG12D-driven genetically engineered mouse model of PDA were screened by RT-PCR. We then used a tissue microarray to survey STAG2 protein expression levels in 344 human PDA tumor samples and adjacent tissues. Univariate Kaplan Meier analysis and multivariate Cox Regression analysis were used to assess the association of STAG2 expression relative to overall survival and response to adjuvant therapy. Finally, RNAi-based assays with PDA cell lines were used to assess the potential therapeutic consequence of STAG2 expression in response to 18 therapeutic agents. Results STAG2 is targeted by somatic aberrations in a subset (4%) of human PDAs. Transposon-mediated disruption of STAG2 in a KRASG12D genetically engineered mouse model promotes the development of PDA and its progression to metastatic disease. There was a statistically significant loss of STAG2 protein expression in human tumor tissue (Wilcoxon-Rank test) with complete absence of STAG2 staining observed in 15 (4.3%) patients. In univariate Kaplan Meier analysis nearly complete STAG2 positive staining (>95% of nuclei positive) was associated with a median survival benefit of 6.41 months (P = 0.031). The survival benefit of adjuvant chemotherapy was only seen in patients with a STAG2 staining of less than 95% (median survival benefit 7.65 months; P = 0.028). Multivariate Cox Regression analysis showed that STAG2 is an independent prognostic factor for survival in pancreatic cancer patients. Finally, we show that RNAi-mediated knockdown of STAG2 selectively sensitizes human PDA cell lines to platinum-based therapy. Conclusions Based on these iterative findings we propose that STAG2 is a clinically significant tumor suppressor in PDA

Homology-based inference sets the bar high for protein function prediction

Background: Any method that de novo predicts protein function should do better than random. More challenging, it also ought to outperform simple homology-based inference. Methods: Here, we describe a few methods that predict protein function exclusively through homology. Together, they set the bar or lower limit for future improvements. Results and conclusions: During the development of these methods, we faced two surprises. Firstly, our most successful implementation for the baseline ranked very high at CAFA1. In fact, our best combination of homology-based methods fared only slightly worse than the top-of-the-line prediction method from the Jones group. Secondly, although the concept of homology-based inference is simple, this work revealed that the precise details of the implementation are crucial: not only did the methods span from top to bottom performers at CAFA, but also the reasons for these differences were unexpected. In this work, we also propose a new rigorous measure to compare predicted and experimental annotations. It puts more emphasis on the details of protein function than the other measures employed by CAFA and may best reflect the expectations of users. Clearly, the definition of proper goals remains one major objective for CAFA

Body Fluid Cytokine Levels in Mild Cognitive Impairment and Alzheimer’s Disease: a Comparative Overview

This article gives a comprehensive overview of cytokine and other inflammation associated protein levels in plasma, serum and cerebrospinal fluid (CSF) of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). We reviewed 118 research articles published between 1989 and 2013 to compare the reported levels of 66 cytokines and other proteins related to regulation and signaling in inflammation in the blood or CSF obtained from MCI and AD patients. Several cytokines are evidently regulated in (neuro-) inflammatory processes associated with neurodegenerative disorders. Others do not display changes in the blood or CSF during disease progression. However, many reports on cytokine levels in MCI or AD are controversial or inconclusive, particularly those which provide data on frequently investigated cytokines like tumor necrosis factor alpha (TNF-α) or interleukin-6 (IL-6). The levels of several cytokines are possible indicators of neuroinflammation in AD. Some of them might increase steadily during disease progression or temporarily at the time of MCI to AD conversion. Furthermore, elevated body fluid cytokine levels may correlate with an increased risk of conversion from MCI to AD. Yet, research results are conflicting. To overcome interindividual variances and to obtain a more definite description of cytokine regulation and function in neurodegeneration, a high degree of methodical standardization and patients collective characterization, together with longitudinal sampling over years is essential

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Application of the Taylor Equation to Five-Power-Law Creep Considering the Influence of Solutes

This study determines the feasibility of describing the flow stress within the five-power-law creep regime, using a linear superposition of a dislocation hardening term and a significant solute strengthening term. It is assumed that the solutes are randomly distributed. It was found that by using an energy balance approach, the flow stress at high temperatures can be well-described by the classic Taylor equation with a solute strengthening term, τo, that is added to the αMGbρ1/2 dislocation hardening term